Free aggregate pulse: how many entities newly needed coverage in the window, broken down by source, lead-value tier, and coverage line — with a small redacted sample. No contact data.
| Name | Required | Description | Default |
|---|---|---|---|
| days | No | ||
| state | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the burden of behavioral disclosure. It reveals the output type (aggregate counts, redacted sample) and constraints (no contact data), but does not explicitly state read-only nature, permissions, or rate limits. It is adequate but not comprehensive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that conveys the core functionality and constraints efficiently. It avoids unnecessary words and earns its place, though it could be slightly more structured (e.g., listing parameters).
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 2 parameters (0% schema coverage) and no output schema or annotations, the description is incomplete. It explains what the tool returns but does not specify parameter semantics, return format, or usage context relative to siblings. More detail is needed for a fully self-contained description.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not explain the 'days' and 'state' parameters. The term 'window' in the description may relate to days but is not explicit. The description adds no semantic value to the parameters, making it difficult for an agent to know how to set them correctly.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: providing aggregate counts of entities that newly needed coverage, with breakdowns by source, lead-value tier, and coverage line, plus a redacted sample. It distinguishes itself from sibling tools like coverage_sources and coverage_trigger_feed by focusing on aggregate pulse rather than detailed sources or feeds.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for obtaining aggregated coverage insights without contact data, but does not explicitly state when to use this tool versus alternatives like coverage_sources or coverage_trigger_feed. There is no guidance on when not to use it or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool has a clearly distinct purpose: coverage_pulse provides an aggregate overview without contact data, coverage_sources lists metadata about trigger sources, and coverage_trigger_feed returns actual business leads. No overlap in functionality.
All tool names follow a consistent 'coverage_[noun]' pattern (coverage_pulse, coverage_sources, coverage_trigger_feed), making it easy to predict the purpose from the name.
Three tools are well-scoped for the server's purpose—providing aggregate insights, source metadata, and the actual lead feed. Not too few or too many for a focused lead-generation domain.
The tool surface covers the essential operations: understanding aggregate demand (pulse), learning about data sources (sources), and retrieving actual leads (feed). No obvious gaps for the intended use case.